Aiming at simulates the human visual system to discover the common and salient objects from a group of relevant images, co-salient object detection (CoSOD) often serves as a preliminary step for various down-streaming computer vision tasks, e.g., image co-segmentation [1]}, co-localization [2]}, [3]} and person re-identiﬁcation [4]}. Unlike the standard salient object detection (SOD) which only focuses on the attractive regions from a single image, CoSOD also needs to leverage the similar attributes shared by objects in image group to distinguish the real common objects under the presence of noise objects.
Although the co-salient objects share the same semantic category, their explicit category attributes are unknown in CoSOD task. That is to say, CoSOD methods are not supposed to model the consistency relations of common objects by using the supervision of specific category labels or other information like temporal relations, which is quite different from video sequences tasks [5]}, [6]}. These unique features make CoSOD an emerging and challenging task which has been rapidly growing in recent few years [7]}, [8]}, [9]}.
